
Freebase 15k-237 is a standard benchmark used for knowledge base completion [1]}.
In this work, we use Freebase 15k-237 as a semi-synthetic testbed to evaluate the impact of adversarial regularization.
Taking the entity attribute labels from [2]}, we used the 3-most common attribute labels (e.g., /award/award_nominee) as “sensitive” attributes.
The goal in this dataset is to perform the standard knowledge base completion task, while having the entity embeddings be invariant with respect to these “sensitive” attribute labels.
While synthetic, this dataset provides a useful reference point due to its popularity in the graph embedding literature.
